Accelerating SD Turbo and SDXL Turbo Inference with ONNX Runtime and Olive

we're spending too much time pushing GPUs when we should be optimizing the execution pipeline. using onnx runtime and olive to speed up sd turbo inference isn't some flashy new feature; it's just making existing models run faster on commodity hardware. it cuts down latency and reduces operational costs, which is what the business cares about.

the math shows these tools are effective, cutting inference time by maybe 30-50% depending on the batch size. it’s about smart deployment, not brute force compute. stop over-provisioning and start optimizing the actual execution layer.